MétaCan
Menu
← Back to cohort
Record W4254544694 · doi:10.32920/ryerson.14647746.v1

Counterfactual thinking and repetitive thought in social anxiety

2021· preprint· en· W4254544694 on OpenAlexaff
Jennifer Monforton

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of WindsorToronto Metropolitan University
Fundersnot available
KeywordsCounterfactual thinkingSocial anxietyPsychologyMoodRuminationClinical psychologyAnxietyDevelopmental psychologyCognitionPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Research suggests that those experiencing Social Anxiety (SA) symptoms are more likely to engage in repetitive thought (RT), including upward counterfactual thinking (U-CFT). Findings indicate that these cognitive patterns may lead to deleterious thoughts and emotions, particularly when U-CFT focuses on non-repeatable, uncontrollable situations and negative self-appraisals. The present dissertation consisted of two complementary studies. Study 1 attempted to 1) validate new measures of state and trait U-CFT, 2) examine the relationship between U-CFT and established measures of RT and mood, and 3) explore the relationship between SA symptoms and counterfactual thinking within a student population. Results indicated that the U-CFT-S (trait measure of U-CFT) and the Counterfactual Likelihood scales (state measure of U-CFT) evidenced sound psychometrics in terms of internal consistency, factor structure, and relationships with related questionnaires. Factor analyses revealed that the Maladaptive U-CFT-S scale clustered with negative mood, rumination, and learned helplessness, while the Adaptive U-CFT subscale clustered with measures of positive mood and self-efficacy. Finally, symptoms of SA correlated positively with state and trait U-CFT generation. Study 2 1) compared patterns of U-CFT and emotions such as guilt and self-blame between a diagnosed Social Anxiety Disorder (SAD) group and a Healthy Control (HC) group 2) determined if disorder-specific content impacts U-CFT generation, and 3) piloted a brief, CBT-based, video intervention targeting maladaptive U-CFT. Results indicated that the SAD group evidenced higher amounts of U-CFT in response to the socially-based scenarios than the HC group and in response to social than non-social scenarios. The SAD group evidenced higher levels of unhelpful emotions (e.g., guilt) both pre- and post-CFT generation than HC participants. Finally, the CBT intervention was generally unsuccessful at reducing maladaptive U-CFT, but was more likely to be effective among SAD than HC participants. Implications of this dissertation include: 1) the benefit of including state- and trait-based measures of U-CFT in future research, 2) the importance of conceptualizing U-CFT as a multifaceted construct, 3) addressing that those with SAD are engaging in maladaptive U-CFT and experiencing consequent guilt and self-blame, and 4) the direction of creating more comprehensive, brief interventions aimed at targeting maladaptive U-CFT.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.042
GPT teacher head0.357
Teacher spread0.316 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes→French-language works237,207→