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Record W2061950258 · doi:10.1016/j.pain.2004.06.018

Anxiety sensitivity, fear, and avoidance behavior in headache pain

2004· article· en· W2061950258 on OpenAlexafffund
Peter J. Norton, Gordon J. G. Asmundson

Bibliographic record

VenuePain · 2004
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Regina
FundersCanadian Institutes of Health Research
KeywordsHeadachesAnxietyAnxiety sensitivityPsychologyAvoidance behaviourPain catastrophizingChronic painClinical psychologyPsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

Recent research has implicated anxiety sensitivity (AS), the fear of anxiety-related sensations, as a mitigating factor involved in fear and avoidance in patients with chronic back pain [Understanding and treating fear of pain (2004) 3]. Given reported similarities between individuals experiencing chronic pain and those experiencing recurrent headaches, it is theoretically plausible that AS plays a role in influencing fear of pain and avoidance behavior in people with recurrent headache. This has not been studied to date. In the current study we used structural equation modeling to examine the role of AS in fear and avoidance behavior of patients experiencing recurrent headaches. Treatment seeking patients with recurrent headaches completed measures of AS, headache pain severity, pain-related fear, and pain-related escape and avoidance behavior. Structural equation modeling supported the prediction of a direct significant loading of AS on fear of pain. Headache severity also had a direct loading on fear of pain. Results also revealed that AS and headache severity had indirect relationships to pain-related escape and avoidance via their direct loadings on fear of pain. Headache severity also had a small direct loading on escape and avoidance behavior. These results provide compelling evidence that AS may play an important role in pain-related fear and escape and avoidance behavior in patients with recurrent headaches.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.286
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
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 head0.010
GPT teacher head0.269
Teacher spread0.259 · 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

Citations152
Published2004
Admission routes2
Has abstractyes

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