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Record W4231181747 · doi:10.32920/ryerson.14645520

Cognitive Strategies for Management of Social Anxiety: A Comparison of Brief Cognitive Restructuring and Mindfulness Interventions

2021· preprint· en· W4231181747 on OpenAlexaff
Leorra Newman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsMindfulnessCognitive restructuringAnxietyPsychologySocial anxietyCognitionPsychological interventionClinical psychologyPsychotherapistModalitiesRandomized controlled trialCognitive therapyPsychiatryMedicine

Abstract

fetched live from OpenAlex

The gold standard psychological treatment for social anxiety disorder (SAD), one of the most common anxiety disorders, is cognitive-behavioural therapy (CBT), incorporating cognitive restructuring to target maladaptive beliefs thought to maintain SAD. Recent evidence suggests that mindfulness- and acceptance-based approaches, emphasizing nonjudgmental awareness without active pursuit of cognitive change, may also be effective. The goal of the current study was to examine the mechanisms by which each cognitive approach affects symptoms. Eighty-seven adults with elevated social anxiety were randomized to receive training in one of the strategies or to a control condition in which participants completed assessments only. Participants self-reported similar decreases in symptoms after 1 week of practice, and these improvements were mediated by increases in decentering and decreases in maladaptive beliefs across condition. These results suggest greater overlap between modalities than theory might predict. Implications for clinical practice, including brief treatments and the role of assessment, are reviewed.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.103
GPT teacher head0.438
Teacher spread0.336 · 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 designRandomized trial
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

Citations0
Published2021
Admission routes1
Has abstractyes

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