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Record W2972010936 · doi:10.29252/jcmh.6.2.16

Positive/ Negative Affect, Strategies of Cognitive Emotion Regulation and Alexithymia in Female Patients with Migraine Headache

2019· article· en· W2972010936 on OpenAlexaboutno aff
Azra Zebardast, Mahdiyeh Shafieetabar

Bibliographic record

VenueQuarterly Journal of Child Mental Health · 2019
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaAffect (linguistics)MigraineCognitionPsychologyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The most common headache, migraine, is a recurring and pulsing pain together with nausea, which may last for 4 to 72 hours. Since migraine has multiple biological, psychological, and environmental causes, it is considered a chronic disease by health psychologists. This comparative and investigative research aims to answer this essential question that whether positive and negative affections, cognitive emotion regulation strategies, and alexithymia as the psychological mechanisms are different in adolescent girls with and without migraine? Method: This research was a descriptive study of casual-comparative design. The sample consisted of two groups of girls with and without migraine, who were selected by convenience sampling and purposeful technique from therapeutic centers of Arak in 2017 (40 individuals per group). The participants completed Toronto Alexithymia Scale-20 (Bagbi, Parker, & Taylor, 1994), Cognitive Emotion Regulation Questionnaire (Garfenski, Kraaji, & Spin-hoven, 2002), and Positive and Negative Affect Schedule (Watson, Clark, & Tellegen, 1998). T-test and multivariate analysis of variance were used to analyze the data.

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)0.000
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 score0.022
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.270
Teacher spread0.263 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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