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Record W2069795020 · doi:10.1037/0022-0167.48.2.123

Guided imagery and memory: Implications for psychotherapists.

2001· article· en· W2069795020 on OpenAlexaff
Katherine D. Arbuthnott, Dennis W. Arbuthnott, Lucille Rossiter

Bibliographic record

VenueJournal of Counseling Psychology · 2001
Typearticle
Languageen
FieldPsychology
TopicPsychological Testing and Assessment
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPsychologyGuided imageryCognitive psychologyMental imagePsychotherapistPsychoanalysisCognitionAnxiety

Abstract

fetched live from OpenAlex

Imagery techniques involve the mental generation of perceptual experiences in the absence of external perceptual stimulation. Such techniques are used for many purposes in psychotherapy but have recently come under attack as a risky practice that may result in memory distortion or the creation of false memories. This article reviews research linking imagery with changes in memory, both to sensitize clinicians to possible inappropriate applications of guided imagery techniques and to discourage researchers from understating the potential utility of guided imagery. The implications of this research for the psychotherapeutic use of imagery are discussed, and strategies for using imagery while reducing the potential for memory distortion are described.

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)0.002
metaresearch head score (Gemma)0.011
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: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.008
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.118
GPT teacher head0.465
Teacher spread0.347 · 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
GenreCommentary

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

Citations65
Published2001
Admission routes1
Has abstractyes

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