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Record W2104910793 · doi:10.1002/da.20418

The effect of the cognitive style of acceptance on negative mood in a recovered depressed sample

2008· article· en· W2104910793 on OpenAlexaff
Alisa R. Singer, Keith S. Dobson

Bibliographic record

VenueDepression and Anxiety · 2008
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsAlberta Health ServicesUniversity of Calgary
Fundersnot available
KeywordsPsychologySelf-acceptanceSadnessMoodFeelingAnxietyClinical psychologyAcceptance and commitment therapyCognitionSample (material)Social psychologyAngerPsychiatryIntervention (counseling)

Abstract

fetched live from OpenAlex

BACKGROUND: This study employed an experimental design to examine: (1) the predictors of the ability to engage in acceptance in individuals with a history of depression, and (2) the effect of acceptance on a negative mood state and altering attitudes toward feeling sad. METHODS: Sixty-five recovered depressed participants received instruction in the metacognitive style of acceptance before a negative mood induction. The degree to which the participants engaged in acceptance was then rated by independent raters. RESULTS: Forty percent of the sample failed to adhere to an attitude of acceptance. Participants with higher levels of anxiety and greater negative attitudes toward sadness were less able to engage in acceptance. Participants who optimally engaged in acceptance demonstrated greater reduction in their negative mood and increased metacognitive beliefs about acceptance after the use of the technique compared to those who failed to adhere to acceptance. CONCLUSIONS: These results imply that acceptance can be difficult to learn, and there may be identifiable individual differences that predict the ability to engage in acceptance. The implications of these results for future research and clinical practice 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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
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 head0.019
GPT teacher head0.307
Teacher spread0.288 · 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 designObservational
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

Citations24
Published2008
Admission routes1
Has abstractyes

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