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Record W2268392893 · doi:10.1155/2002/564743

The Role of Health Anxiety among Patients with Chronic Pain in Determining Response to Therapy

2002· article· en· W2268392893 on OpenAlexaff
Heather D. Hadjistavropoulos, Gordon J. G. Asmundson, Diane L. LaChapelle, Allisson Quine

Bibliographic record

VenuePain Research and Management · 2002
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsAnxietyChronic painMedicinePhysical therapyClinical psychologyPsychologyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Considerable research suggests that health anxiety (HA) influences the response of patients with chronic pain to pain and treatment. The present investigation extends the current understanding of HA and explores whether it affects how patients respond to a common therapeutic intervention, namely instructions to reduce pain behaviour. Sixty-five patients with chronic pain completed measures of pain, anxiety and cognition following an active occupational therapy session in which they were specifically instructed either to inhibit or reduce pain behaviour, or to carry out the session as they normally would. Regression analyses revealed that those with higher levels of HA experienced greater anxiety, somatic sensations and catastrophic cognitions during therapy than those with lower levels of HA. The regression analyses also revealed a consistent trend for an interaction between HA and instructional set; when those with higher HA reduced their pain behaviour, they subsequently reported greater anxiety, and more somatic sensations and catastrophic thoughts than when they carried out the session as they normally would. In contrast, only those with lower HA had a tendency to benefit from reducing pain behaviour, reporting lower state anxiety and fewer somatic sensations during the session than those who did not reduce their pain behaviour. The results suggest that HA should be taken into consideration during treatment.

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)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.000
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 head0.021
GPT teacher head0.318
Teacher spread0.297 · 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

Citations13
Published2002
Admission routes1
Has abstractyes

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