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Record W2409528975 · doi:10.1080/00223891.2016.1178650

Assessing Anger Expression: Construct Validity of Three Emotion Expression-Related Measures

2016· article· en· W2409528975 on OpenAlex
Matthew J. Jasinski, Mark A. Lumley, Deborah V. Latsch, Erik Schuster, Ellen Kinner, John W. Burns

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Personality Assessment · 2016
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsAngerAlexithymiaPsychologyToronto Alexithymia ScaleDiscriminant validityEmotional expressionConstruct validityConvergent validityCoping (psychology)HostilityRuminationTest validityExpression (computer science)Clinical psychologyPsychometricsPsychiatryDevelopmental psychologyCognition

Abstract

fetched live from OpenAlex

Self-report measures of emotional expression are common, but their validity to predict objective emotional expression, particularly of anger, is unclear. We tested the validity of the Anger Expression Inventory (AEI; Spielberger et al., 1985 Spielberger, C. D., Johnson, E. H., Russell, S. F., Crane, R. J., Jacobs, G. A., & Wordern, T. J. (1985). The experience and expression of anger: Construction and validation of an anger expression scale. In M. A. Chesney & R. H. Rosenman (Eds.), Anger and hostility in cardiovascular and behavioral disorders (pp. 5–30). New York, NY: Hemisphere. [Google Scholar]), Emotional Approach Coping Scale (EAC; Stanton, Kirk, Cameron, & Danoff-Burg, 2000 Stanton, A. L., Kirk, S. B., Cameron, C. L., & Danoff-Burg, S. (2000). Coping through emotional approach: Scale construction and validation. Journal of Personality and Social Psychology, 78, 1150–1169. doi:10.1037/0022-3514.78.6.1150[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]), and Toronto Alexithymia Scale-20 (TAS-20; Bagby, Taylor, & Parker, 1994 Bagby, R. M., Taylor, G. J., & Parker, J. D. (1994). The twenty-item Toronto Alexithymia Scale-II. Convergent, discriminant, and concurrent validity. Journal of Psychosomatic Research, 38, 33–40. doi:10.1016/0022-3999(94)90006-X[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) to predict objective anger expression in 95 adults with chronic back pain. Participants attempted to solve a difficult computer maze by following the directions of a confederate who treated them rudely and unjustly. Participants then expressed their feelings for 4 min. Blinded raters coded the videos for anger expression, and a software program analyzed expression transcripts for anger-related words. Analyses related each questionnaire to anger expression. The AEI Anger-Out scale predicted greater anger expression, as expected, but AEI Anger-In did not. The EAC Emotional Processing scale predicted less anger expression, but the EAC Emotional Expression scale was unrelated to anger expression. Finally, the TAS-20 predicted greater anger expression. Findings support the validity of the AEI Anger-Out scale but raise questions about the other measures. The assessment of emotional expression by self-report is complex and perhaps confounded by general emotional experience, the specificity or generality of the emotion(s) assessed, and self-awareness limitations. Performance-based or clinician-rated measures of emotion expression are needed.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.129
GPT teacher head0.404
Teacher spread0.275 · 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